Overview

Brought to you by YData

Dataset statistics

Number of variables40
Number of observations19919
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 MiB
Average record size in memory105.0 B

Variable types

Numeric10
Categorical1
Boolean29

Alerts

joined_through_referral_No is highly overall correlated with joined_through_referral_YesHigh correlation
joined_through_referral_Yes is highly overall correlated with joined_through_referral_NoHigh correlation
medium_of_operation_Desktop is highly overall correlated with medium_of_operation_SmartphoneHigh correlation
medium_of_operation_Smartphone is highly overall correlated with medium_of_operation_DesktopHigh correlation
offer_application_preference_Yes is highly overall correlated with used_special_discount_YesHigh correlation
preferred_offer_types_Gift Vouchers/Coupons is highly overall correlated with preferred_offer_types_Without OffersHigh correlation
preferred_offer_types_Without Offers is highly overall correlated with preferred_offer_types_Gift Vouchers/CouponsHigh correlation
used_special_discount_Yes is highly overall correlated with offer_application_preference_YesHigh correlation
gender_Unknown is highly imbalanced (98.1%) Imbalance
medium_of_operation_Both is highly imbalanced (51.6%) Imbalance
feedback_Products always in Stock is highly imbalanced (76.2%) Imbalance
feedback_Quality Customer Care is highly imbalanced (76.7%) Imbalance
feedback_Reasonable Price is highly imbalanced (76.0%) Imbalance
feedback_User Friendly Website is highly imbalanced (78.3%) Imbalance
last_visit_time_hour has 846 (4.2%) zeros Zeros
last_visit_time_minutes has 361 (1.8%) zeros Zeros
last_visit_time_seconds has 332 (1.7%) zeros Zeros

Reproduction

Analysis started2025-03-01 08:17:48.589500
Analysis finished2025-03-01 08:18:06.084324
Duration17.49 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

age
Real number (ℝ)

Distinct55
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.884432
Minimum10
Maximum64
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size155.7 KiB
2025-03-01T13:48:06.362422image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile12
Q123
median37
Q351
95-th percentile62
Maximum64
Range54
Interquartile range (IQR)28

Descriptive statistics

Standard deviation15.917311
Coefficient of variation (CV)0.4315455
Kurtosis-1.2076972
Mean36.884432
Median Absolute Deviation (MAD)14
Skewness0.0087148231
Sum734701
Variance253.36078
MonotonicityNot monotonic
2025-03-01T13:48:06.486780image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
58 396
 
2.0%
47 396
 
2.0%
34 393
 
2.0%
17 386
 
1.9%
13 385
 
1.9%
27 383
 
1.9%
41 383
 
1.9%
25 379
 
1.9%
39 379
 
1.9%
23 379
 
1.9%
Other values (45) 16060
80.6%
ValueCountFrequency (%)
10 357
1.8%
11 378
1.9%
12 357
1.8%
13 385
1.9%
14 358
1.8%
15 378
1.9%
16 364
1.8%
17 386
1.9%
18 371
1.9%
19 374
1.9%
ValueCountFrequency (%)
64 361
1.8%
63 377
1.9%
62 346
1.7%
61 370
1.9%
60 359
1.8%
59 340
1.7%
58 396
2.0%
57 358
1.8%
56 332
1.7%
55 359
1.8%

days_since_last_login
Real number (ℝ)

Distinct27
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-39.216527
Minimum-999
Maximum26
Zeros0
Zeros (%)0.0%
Negative1022
Negative (%)5.1%
Memory size155.7 KiB
2025-03-01T13:48:06.599473image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-999
5-th percentile-999
Q18
median12
Q316
95-th percentile22
Maximum26
Range1025
Interquartile range (IQR)8

Descriptive statistics

Standard deviation223.27442
Coefficient of variation (CV)-5.6933757
Kurtosis14.528121
Mean-39.216527
Median Absolute Deviation (MAD)4
Skewness-4.0638369
Sum-781154
Variance49851.467
MonotonicityNot monotonic
2025-03-01T13:48:06.695043image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
14 1298
 
6.5%
12 1290
 
6.5%
13 1278
 
6.4%
11 1274
 
6.4%
15 1241
 
6.2%
10 1177
 
5.9%
16 1084
 
5.4%
9 1031
 
5.2%
-999 1022
 
5.1%
8 914
 
4.6%
Other values (17) 8310
41.7%
ValueCountFrequency (%)
-999 1022
5.1%
1 177
 
0.9%
2 343
 
1.7%
3 404
 
2.0%
4 534
2.7%
5 632
3.2%
6 686
3.4%
7 803
4.0%
8 914
4.6%
9 1031
5.2%
ValueCountFrequency (%)
26 42
 
0.2%
25 122
 
0.6%
24 252
 
1.3%
23 373
1.9%
22 449
2.3%
21 520
2.6%
20 622
3.1%
19 685
3.4%
18 772
3.9%
17 894
4.5%

avg_time_spent
Real number (ℝ)

Distinct15703
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean244.13493
Minimum-2180.7808
Maximum3350.06
Zeros0
Zeros (%)0.0%
Negative931
Negative (%)4.7%
Memory size155.7 KiB
2025-03-01T13:48:06.776869image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-2180.7808
5-th percentile30.13
Q159.36
median161.24
Q3354.195
95-th percentile1045.8049
Maximum3350.06
Range5530.8408
Interquartile range (IQR)294.835

Descriptive statistics

Standard deviation403.91081
Coefficient of variation (CV)1.6544573
Kurtosis5.3563369
Mean244.13493
Median Absolute Deviation (MAD)122.75
Skewness0.6757712
Sum4862923.6
Variance163143.94
MonotonicityNot monotonic
2025-03-01T13:48:06.894497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32.41 13
 
0.1%
33.38 11
 
0.1%
31.33 11
 
0.1%
31.37 11
 
0.1%
34.23 11
 
0.1%
32.36 10
 
0.1%
31.74 10
 
0.1%
34.73 10
 
0.1%
30.3 10
 
0.1%
30.28 10
 
0.1%
Other values (15693) 19812
99.5%
ValueCountFrequency (%)
-2180.780796 1
< 0.1%
-2069.765095 1
< 0.1%
-2041.955137 1
< 0.1%
-2020.211586 1
< 0.1%
-1865.148353 1
< 0.1%
-1863.380252 1
< 0.1%
-1846.976159 1
< 0.1%
-1838.166358 1
< 0.1%
-1826.229187 1
< 0.1%
-1747.660522 1
< 0.1%
ValueCountFrequency (%)
3350.06 1
< 0.1%
3218.15 1
< 0.1%
3005.45 1
< 0.1%
2830.522122 1
< 0.1%
2821.700394 1
< 0.1%
2816.81 1
< 0.1%
2732.248684 1
< 0.1%
2727.32266 1
< 0.1%
2661.74 1
< 0.1%
2584.97 1
< 0.1%

avg_transaction_value
Real number (ℝ)

Distinct19883
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29318.122
Minimum803.71
Maximum99995.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size155.7 KiB
2025-03-01T13:48:07.003011image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum803.71
5-th percentile3406.184
Q114236.2
median27564.05
Q340969.4
95-th percentile67783.568
Maximum99995.03
Range99191.32
Interquartile range (IQR)26733.2

Descriptive statistics

Standard deviation19507.775
Coefficient of variation (CV)0.66538284
Kurtosis1.4300573
Mean29318.122
Median Absolute Deviation (MAD)13373.84
Skewness1.0073729
Sum5.8398768 × 108
Variance3.805533 × 108
MonotonicityNot monotonic
2025-03-01T13:48:07.111046image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30549.39 2
 
< 0.1%
29126.49 2
 
< 0.1%
30466.15 2
 
< 0.1%
25675.32 2
 
< 0.1%
35273.37 2
 
< 0.1%
7446.19 2
 
< 0.1%
31237.68 2
 
< 0.1%
19954.77 2
 
< 0.1%
19753.04 2
 
< 0.1%
13897.26 2
 
< 0.1%
Other values (19873) 19899
99.9%
ValueCountFrequency (%)
803.71 1
< 0.1%
807.4 1
< 0.1%
808.8 1
< 0.1%
813.22 1
< 0.1%
818.2 1
< 0.1%
820.55 1
< 0.1%
823.83 1
< 0.1%
824.36 1
< 0.1%
824.96 1
< 0.1%
828.2 1
< 0.1%
ValueCountFrequency (%)
99995.03 1
< 0.1%
99926.55 1
< 0.1%
99920.48 1
< 0.1%
99868.18 1
< 0.1%
99853.72 1
< 0.1%
99839.14 1
< 0.1%
99832.04 1
< 0.1%
99825.11 1
< 0.1%
99761.63 1
< 0.1%
99704.14 1
< 0.1%

points_in_wallet
Real number (ℝ)

Distinct14582
Distinct (%)73.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean685.96879
Minimum-465.28998
Maximum2019.6716
Zeros0
Zeros (%)0.0%
Negative61
Negative (%)0.3%
Memory size155.7 KiB
2025-03-01T13:48:07.329397image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-465.28998
5-th percentile345.47204
Q1624.48
median685.96879
Q3757.855
95-th percentile1018.9025
Maximum2019.6716
Range2484.9616
Interquartile range (IQR)133.375

Descriptive statistics

Standard deviation182.4387
Coefficient of variation (CV)0.26595772
Kurtosis4.8499807
Mean685.96879
Median Absolute Deviation (MAD)66.971206
Skewness-0.10054995
Sum13663812
Variance33283.878
MonotonicityNot monotonic
2025-03-01T13:48:07.526963image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
685.9687938 1963
 
9.9%
623.92 6
 
< 0.1%
714.22 5
 
< 0.1%
770.5 5
 
< 0.1%
741.42 5
 
< 0.1%
685.8 5
 
< 0.1%
762.37 5
 
< 0.1%
724.29 5
 
< 0.1%
748.36 5
 
< 0.1%
710.88 5
 
< 0.1%
Other values (14572) 17910
89.9%
ValueCountFrequency (%)
-465.2899767 1
< 0.1%
-405.6977897 1
< 0.1%
-391.9431597 1
< 0.1%
-363.1999639 1
< 0.1%
-360.1803683 1
< 0.1%
-333.2670158 1
< 0.1%
-324.9092899 1
< 0.1%
-317.4617767 1
< 0.1%
-308.7707942 1
< 0.1%
-304.5787684 1
< 0.1%
ValueCountFrequency (%)
2019.671602 1
< 0.1%
1830.79742 1
< 0.1%
1783.307652 1
< 0.1%
1736.522643 1
< 0.1%
1730.549571 1
< 0.1%
1728.724436 1
< 0.1%
1696.381767 1
< 0.1%
1681.102378 1
< 0.1%
1634.86111 1
< 0.1%
1634.367256 1
< 0.1%

joining_day
Real number (ℝ)

Distinct31
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.644761
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size77.9 KiB
2025-03-01T13:48:07.737392image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median16
Q323
95-th percentile29
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.7887319
Coefficient of variation (CV)0.56176836
Kurtosis-1.1924375
Mean15.644761
Median Absolute Deviation (MAD)8
Skewness0.019423615
Sum311628
Variance77.241808
MonotonicityNot monotonic
2025-03-01T13:48:07.851378image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
4 724
 
3.6%
9 697
 
3.5%
23 696
 
3.5%
16 683
 
3.4%
18 677
 
3.4%
20 675
 
3.4%
6 668
 
3.4%
22 668
 
3.4%
10 667
 
3.3%
8 666
 
3.3%
Other values (21) 13098
65.8%
ValueCountFrequency (%)
1 656
3.3%
2 662
3.3%
3 625
3.1%
4 724
3.6%
5 631
3.2%
6 668
3.4%
7 649
3.3%
8 666
3.3%
9 697
3.5%
10 667
3.3%
ValueCountFrequency (%)
31 380
1.9%
30 576
2.9%
29 616
3.1%
28 656
3.3%
27 647
3.2%
26 614
3.1%
25 624
3.1%
24 621
3.1%
23 696
3.5%
22 668
3.4%

joining_month
Real number (ℝ)

Distinct12
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.504945
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size77.9 KiB
2025-03-01T13:48:07.940501image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median6
Q310
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.4432795
Coefficient of variation (CV)0.5293326
Kurtosis-1.209962
Mean6.504945
Median Absolute Deviation (MAD)3
Skewness0.0006436224
Sum129572
Variance11.856173
MonotonicityNot monotonic
2025-03-01T13:48:08.044693image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
5 1743
8.8%
11 1716
8.6%
3 1706
8.6%
7 1692
8.5%
10 1679
8.4%
1 1677
8.4%
8 1670
8.4%
4 1655
8.3%
6 1632
8.2%
12 1625
8.2%
Other values (2) 3124
15.7%
ValueCountFrequency (%)
1 1677
8.4%
2 1548
7.8%
3 1706
8.6%
4 1655
8.3%
5 1743
8.8%
6 1632
8.2%
7 1692
8.5%
8 1670
8.4%
9 1576
7.9%
10 1679
8.4%
ValueCountFrequency (%)
12 1625
8.2%
11 1716
8.6%
10 1679
8.4%
9 1576
7.9%
8 1670
8.4%
7 1692
8.5%
6 1632
8.2%
5 1743
8.8%
4 1655
8.3%
3 1706
8.6%

joining_year
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size155.7 KiB
2015
6659 
2017
6639 
2016
6621 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters79676
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015
2nd row2016
3rd row2017
4th row2017
5th row2015

Common Values

ValueCountFrequency (%)
2015 6659
33.4%
2017 6639
33.3%
2016 6621
33.2%

Length

2025-03-01T13:48:08.146468image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-01T13:48:08.230530image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
2015 6659
33.4%
2017 6639
33.3%
2016 6621
33.2%

Most occurring characters

ValueCountFrequency (%)
2 19919
25.0%
0 19919
25.0%
1 19919
25.0%
5 6659
 
8.4%
7 6639
 
8.3%
6 6621
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79676
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 19919
25.0%
0 19919
25.0%
1 19919
25.0%
5 6659
 
8.4%
7 6639
 
8.3%
6 6621
 
8.3%

Most occurring scripts

ValueCountFrequency (%)
Common 79676
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 19919
25.0%
0 19919
25.0%
1 19919
25.0%
5 6659
 
8.4%
7 6639
 
8.3%
6 6621
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79676
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 19919
25.0%
0 19919
25.0%
1 19919
25.0%
5 6659
 
8.4%
7 6639
 
8.3%
6 6621
 
8.3%

last_visit_time_hour
Real number (ℝ)

Zeros 

Distinct24
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.545108
Minimum0
Maximum23
Zeros846
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size155.7 KiB
2025-03-01T13:48:08.297909image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median12
Q318
95-th percentile22
Maximum23
Range23
Interquartile range (IQR)12

Descriptive statistics

Standard deviation6.9028053
Coefficient of variation (CV)0.59789874
Kurtosis-1.1926469
Mean11.545108
Median Absolute Deviation (MAD)6
Skewness-0.0092336845
Sum229967
Variance47.648721
MonotonicityNot monotonic
2025-03-01T13:48:08.378170image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
18 878
 
4.4%
10 870
 
4.4%
12 866
 
4.3%
19 855
 
4.3%
20 846
 
4.2%
0 846
 
4.2%
14 845
 
4.2%
6 839
 
4.2%
11 838
 
4.2%
23 838
 
4.2%
Other values (14) 11398
57.2%
ValueCountFrequency (%)
0 846
4.2%
1 815
4.1%
2 781
3.9%
3 811
4.1%
4 812
4.1%
5 811
4.1%
6 839
4.2%
7 833
4.2%
8 835
4.2%
9 821
4.1%
ValueCountFrequency (%)
23 838
4.2%
22 814
4.1%
21 822
4.1%
20 846
4.2%
19 855
4.3%
18 878
4.4%
17 779
3.9%
16 814
4.1%
15 825
4.1%
14 845
4.2%

last_visit_time_minutes
Real number (ℝ)

Zeros 

Distinct60
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.593554
Minimum0
Maximum59
Zeros361
Zeros (%)1.8%
Negative0
Negative (%)0.0%
Memory size155.7 KiB
2025-03-01T13:48:08.476440image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q114
median30
Q345
95-th percentile57
Maximum59
Range59
Interquartile range (IQR)31

Descriptive statistics

Standard deviation17.379637
Coefficient of variation (CV)0.58727779
Kurtosis-1.2049265
Mean29.593554
Median Absolute Deviation (MAD)15
Skewness-0.0077189747
Sum589474
Variance302.05178
MonotonicityNot monotonic
2025-03-01T13:48:08.598413image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27 374
 
1.9%
8 373
 
1.9%
0 361
 
1.8%
59 361
 
1.8%
33 356
 
1.8%
54 355
 
1.8%
13 355
 
1.8%
58 354
 
1.8%
48 353
 
1.8%
30 349
 
1.8%
Other values (50) 16328
82.0%
ValueCountFrequency (%)
0 361
1.8%
1 300
1.5%
2 321
1.6%
3 349
1.8%
4 336
1.7%
5 345
1.7%
6 296
1.5%
7 339
1.7%
8 373
1.9%
9 314
1.6%
ValueCountFrequency (%)
59 361
1.8%
58 354
1.8%
57 336
1.7%
56 310
1.6%
55 316
1.6%
54 355
1.8%
53 334
1.7%
52 328
1.6%
51 330
1.7%
50 315
1.6%

last_visit_time_seconds
Real number (ℝ)

Zeros 

Distinct60
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.522516
Minimum0
Maximum59
Zeros332
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size155.7 KiB
2025-03-01T13:48:08.715486image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q115
median29
Q344
95-th percentile57
Maximum59
Range59
Interquartile range (IQR)29

Descriptive statistics

Standard deviation17.304787
Coefficient of variation (CV)0.58615556
Kurtosis-1.1944503
Mean29.522516
Median Absolute Deviation (MAD)15
Skewness0.001422494
Sum588059
Variance299.45565
MonotonicityNot monotonic
2025-03-01T13:48:08.827901image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
57 377
 
1.9%
25 364
 
1.8%
23 361
 
1.8%
30 359
 
1.8%
29 356
 
1.8%
34 355
 
1.8%
52 354
 
1.8%
19 352
 
1.8%
3 351
 
1.8%
20 351
 
1.8%
Other values (50) 16339
82.0%
ValueCountFrequency (%)
0 332
1.7%
1 337
1.7%
2 333
1.7%
3 351
1.8%
4 305
1.5%
5 339
1.7%
6 307
1.5%
7 340
1.7%
8 301
1.5%
9 324
1.6%
ValueCountFrequency (%)
59 323
1.6%
58 328
1.6%
57 377
1.9%
56 326
1.6%
55 337
1.7%
54 312
1.6%
53 334
1.7%
52 354
1.8%
51 324
1.6%
50 298
1.5%

gender_M
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
10008 
True
9911 
ValueCountFrequency (%)
False 10008
50.2%
True 9911
49.8%
2025-03-01T13:48:08.926512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

gender_Unknown
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
19883 
True
 
36
ValueCountFrequency (%)
False 19883
99.8%
True 36
 
0.2%
2025-03-01T13:48:08.974038image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
True
10583 
False
9336 
ValueCountFrequency (%)
True 10583
53.1%
False 9336
46.9%
2025-03-01T13:48:09.010113image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
17375 
True
2544 
ValueCountFrequency (%)
False 17375
87.2%
True 2544
 
12.8%
2025-03-01T13:48:09.041816image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
16169 
True
3750 
ValueCountFrequency (%)
False 16169
81.2%
True 3750
 
18.8%
2025-03-01T13:48:09.096714image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
15796 
True
4123 
ValueCountFrequency (%)
False 15796
79.3%
True 4123
 
20.7%
2025-03-01T13:48:09.128833image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
17521 
True
2398 
ValueCountFrequency (%)
False 17521
88.0%
True 2398
 
12.0%
2025-03-01T13:48:09.177810image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
17554 
True
2365 
ValueCountFrequency (%)
False 17554
88.1%
True 2365
 
11.9%
2025-03-01T13:48:09.237437image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
16720 
True
3199 
ValueCountFrequency (%)
False 16720
83.9%
True 3199
 
16.1%
2025-03-01T13:48:09.279486image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

joined_through_referral_No
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
11615 
True
8304 
ValueCountFrequency (%)
False 11615
58.3%
True 8304
41.7%
2025-03-01T13:48:09.311035image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

joined_through_referral_Yes
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
11302 
True
8617 
ValueCountFrequency (%)
False 11302
56.7%
True 8617
43.3%
2025-03-01T13:48:09.363415image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
13424 
True
6495 
ValueCountFrequency (%)
False 13424
67.4%
True 6495
32.6%
2025-03-01T13:48:09.394423image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

preferred_offer_types_Without Offers
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
13097 
True
6822 
ValueCountFrequency (%)
False 13097
65.8%
True 6822
34.2%
2025-03-01T13:48:09.444293image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

medium_of_operation_Both
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
17832 
True
2087 
ValueCountFrequency (%)
False 17832
89.5%
True 2087
 
10.5%
2025-03-01T13:48:09.476194image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

medium_of_operation_Desktop
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
12456 
True
7463 
ValueCountFrequency (%)
False 12456
62.5%
True 7463
37.5%
2025-03-01T13:48:09.527638image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

medium_of_operation_Smartphone
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
12514 
True
7405 
ValueCountFrequency (%)
False 12514
62.8%
True 7405
37.2%
2025-03-01T13:48:09.782917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
13346 
True
6573 
ValueCountFrequency (%)
False 13346
67.0%
True 6573
33.0%
2025-03-01T13:48:09.811065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
13320 
True
6599 
ValueCountFrequency (%)
False 13320
66.9%
True 6599
33.1%
2025-03-01T13:48:09.860776image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

used_special_discount_Yes
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
True
10962 
False
8957 
ValueCountFrequency (%)
True 10962
55.0%
False 8957
45.0%
2025-03-01T13:48:09.915350image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

offer_application_preference_Yes
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
True
10945 
False
8974 
ValueCountFrequency (%)
True 10945
54.9%
False 8974
45.1%
2025-03-01T13:48:09.962808image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
True
9969 
False
9950 
ValueCountFrequency (%)
True 9969
50.0%
False 9950
50.0%
2025-03-01T13:48:09.996756image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
16509 
True
3410 
ValueCountFrequency (%)
False 16509
82.9%
True 3410
 
17.1%
2025-03-01T13:48:10.045789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
16545 
True
3374 
ValueCountFrequency (%)
False 16545
83.1%
True 3374
 
16.9%
2025-03-01T13:48:10.077240image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
16618 
True
3301 
ValueCountFrequency (%)
False 16618
83.4%
True 3301
 
16.6%
2025-03-01T13:48:10.127772image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
19141 
True
 
778
ValueCountFrequency (%)
False 19141
96.1%
True 778
 
3.9%
2025-03-01T13:48:10.163501image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
19164 
True
 
755
ValueCountFrequency (%)
False 19164
96.2%
True 755
 
3.8%
2025-03-01T13:48:10.205209image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

feedback_Reasonable Price
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
19131 
True
 
788
ValueCountFrequency (%)
False 19131
96.0%
True 788
 
4.0%
2025-03-01T13:48:10.241411image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
16518 
True
3401 
ValueCountFrequency (%)
False 16518
82.9%
True 3401
 
17.1%
2025-03-01T13:48:10.278303image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size19.6 KiB
False
19230 
True
 
689
ValueCountFrequency (%)
False 19230
96.5%
True 689
 
3.5%
2025-03-01T13:48:10.319989image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Interactions

2025-03-01T13:48:04.081602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:54.750045image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:55.949548image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:56.942027image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:57.901647image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:58.821073image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:00.064756image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:01.262547image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:02.224951image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:03.101074image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:04.172429image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:54.845814image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:56.053234image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:57.031602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:57.983764image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:58.903339image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:00.165362image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:01.354690image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:02.311790image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:03.198188image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:04.268207image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:54.942490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:56.153186image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:57.121995image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:58.086657image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:59.001979image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:00.253602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:01.448557image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:02.397792image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:03.301463image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:04.527930image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:55.091045image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:56.282614image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:57.213610image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:58.184710image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:59.123134image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:00.385226image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:01.552521image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:02.482851image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:03.416221image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:04.630002image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:55.238120image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:56.369840image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:57.302217image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:58.267348image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:59.213801image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:00.653257image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:01.649963image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:02.566880image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:03.500498image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:04.722667image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:55.350638image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:56.469021image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:57.401030image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:58.365396image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:59.327514image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:00.753075image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:01.770924image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:02.657507image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:03.598016image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:04.816329image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:55.453318image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:56.563902image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:57.499355image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:58.449590image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:59.422102image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:00.844009image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:01.854202image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:02.749325image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:03.711315image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:04.904196image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:55.553296image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:56.648834image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:57.600767image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:58.546644image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:59.502122image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:00.961370image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:01.949199image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:02.835296image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:03.801229image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:05.019049image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:55.641280image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:56.742161image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:57.690307image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:58.633367image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:59.850354image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:01.051084image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:02.033053image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:02.920210image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:03.884951image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:05.113714image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:55.734121image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:56.844590image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:57.796195image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:58.730756image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:47:59.953509image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:01.160594image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:02.122454image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:03.013140image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T13:48:03.990765image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-03-01T13:48:10.436144image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ageavg_time_spentavg_transaction_valuedays_since_last_loginfeedback_Poor Customer Servicefeedback_Poor Product Qualityfeedback_Poor Websitefeedback_Products always in Stockfeedback_Quality Customer Carefeedback_Reasonable Pricefeedback_Too many adsfeedback_User Friendly Websitegender_Mgender_Unknowninternet_option_Mobile_Datainternet_option_Wi-Fijoined_through_referral_Nojoined_through_referral_Yesjoining_dayjoining_monthjoining_yearlast_visit_time_hourlast_visit_time_minuteslast_visit_time_secondsmedium_of_operation_Bothmedium_of_operation_Desktopmedium_of_operation_Smartphonemembership_category_Gold Membershipmembership_category_No Membershipmembership_category_Platinum Membershipmembership_category_Premium Membershipmembership_category_Silver Membershipoffer_application_preference_Yespast_complaint_Yespoints_in_walletpreferred_offer_types_Gift Vouchers/Couponspreferred_offer_types_Without Offersregion_category_Townregion_category_Villageused_special_discount_Yes
age1.0000.0010.0040.0030.0190.0150.0000.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.000-0.007-0.0040.008-0.0090.0090.0020.0100.0110.0080.0000.0130.0000.0000.0000.0000.0000.0220.0040.0090.0000.0000.000
avg_time_spent0.0011.0000.026-0.1030.0140.0100.0250.0150.0140.0000.0040.0150.0000.0000.0000.0000.2220.2240.0030.0000.017-0.0070.0080.0060.2030.0540.0680.0120.0120.0220.0000.0000.0710.0050.0150.0000.0000.0000.0110.073
avg_transaction_value0.0040.0261.000-0.0020.1300.1290.1280.3420.3190.3240.1300.3070.0040.0130.0000.0120.0470.0480.0100.0050.000-0.0070.0060.0030.0090.0200.0230.0760.1470.1560.1630.0400.0400.0000.0940.0480.0530.0000.0430.010
days_since_last_login0.003-0.103-0.0021.0000.0070.0170.0000.0000.0020.0000.0060.0000.0000.0050.0070.0000.0050.000-0.001-0.0040.000-0.0020.005-0.0000.0000.0000.0000.0000.0000.0000.0000.0090.0100.000-0.0200.0000.0000.0000.0000.003
feedback_Poor Customer Service0.0190.0140.1300.0071.0000.2050.2020.0910.0900.0920.2060.0850.0000.0000.0050.0000.0080.0150.0110.0000.0000.0150.0130.0000.0150.0000.0000.0110.0530.0400.0520.0030.0000.0000.0520.0210.0340.0030.0030.012
feedback_Poor Product Quality0.0150.0100.1290.0170.2051.0000.2010.0900.0890.0910.2050.0850.0030.0000.0000.0000.0190.0140.0190.0000.0000.0120.0130.0000.0080.0000.0070.0260.0440.0370.0510.0180.0080.0000.0540.0190.0110.0000.0000.000
feedback_Poor Website0.0000.0250.1280.0000.2020.2011.0000.0890.0880.0900.2020.0840.0000.0000.0000.0010.0000.0070.0100.0140.0000.0000.0000.0150.0000.0090.0090.0280.0370.0500.0320.0120.0130.0000.0540.0050.0130.0000.0050.000
feedback_Products always in Stock0.0000.0150.3420.0000.0910.0900.0891.0000.0390.0400.0910.0370.0000.0000.0000.0000.0450.0420.0000.0130.0150.0100.0000.0000.0030.0120.0160.0550.1020.1050.1130.0250.0170.0000.1320.0360.0360.0000.0190.011
feedback_Quality Customer Care0.0000.0140.3190.0020.0900.0890.0880.0391.0000.0390.0890.0360.0000.0000.0020.0000.0380.0350.0140.0000.0000.0000.0000.0140.0110.0090.0150.0520.1010.0920.1200.0200.0280.0000.1430.0300.0430.0090.0230.000
feedback_Reasonable Price0.0000.0000.3240.0000.0920.0910.0900.0400.0391.0000.0910.0370.0000.0000.0130.0070.0150.0120.0130.0120.0000.0220.0020.0000.0000.0070.0120.0640.1030.1170.1040.0370.0210.0000.1450.0310.0400.0080.0280.000
feedback_Too many ads0.0130.0040.1300.0060.2060.2050.2020.0910.0890.0911.0000.0850.0120.0080.0000.0070.0100.0050.0160.0000.0000.0000.0000.0000.0000.0150.0130.0240.0320.0380.0390.0000.0190.0000.0600.0000.0000.0000.0100.011
feedback_User Friendly Website0.0000.0150.3070.0000.0850.0850.0840.0370.0360.0370.0851.0000.0070.0000.0000.0000.0310.0300.0140.0120.0070.0040.0000.0000.0110.0070.0170.0380.0960.1160.0990.0180.0370.0000.1300.0330.0280.0000.0110.010
gender_M0.0000.0000.0040.0000.0000.0030.0000.0000.0000.0000.0120.0071.0000.0410.0070.0190.0040.0000.0000.0000.0000.0200.0240.0070.0000.0000.0050.0000.0000.0030.0000.0000.0000.0000.0160.0000.0000.0000.0050.000
gender_Unknown0.0000.0000.0130.0050.0000.0000.0000.0000.0000.0000.0080.0000.0411.0000.0000.0000.0000.0070.0000.0000.0000.0000.0160.0000.0000.0020.0030.0070.0050.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.000
internet_option_Mobile_Data0.0000.0000.0000.0070.0050.0000.0000.0000.0020.0130.0000.0000.0070.0001.0000.4940.0000.0000.0000.0020.0090.0000.0000.0000.0000.0000.0040.0130.0050.0170.0000.0120.0000.0000.0140.0040.0210.0000.0000.000
internet_option_Wi-Fi0.0000.0000.0120.0000.0000.0000.0010.0000.0000.0070.0070.0000.0190.0000.4941.0000.0000.0000.0000.0130.0000.0000.0000.0060.0000.0000.0000.0000.0000.0100.0000.0140.0130.0060.0000.0090.0090.0000.0000.006
joined_through_referral_No0.0000.2220.0470.0050.0080.0190.0000.0450.0380.0150.0100.0310.0040.0000.0000.0001.0000.7380.0000.0020.0130.0000.0000.0190.0510.0080.0160.0030.0160.0000.0310.0000.0000.0000.0250.0000.0000.0070.0000.020
joined_through_referral_Yes0.0000.2240.0480.0000.0150.0140.0070.0420.0350.0120.0050.0300.0000.0070.0000.0000.7381.0000.0000.0220.0110.0000.0000.0000.0570.0110.0180.0000.0150.0170.0230.0100.0120.0000.0230.0000.0000.0000.0000.019
joining_day-0.0070.0030.010-0.0010.0110.0190.0100.0000.0140.0130.0160.0140.0000.0000.0000.0000.0000.0001.0000.0070.0000.002-0.005-0.0010.0000.0000.0000.0100.0150.0180.0000.0000.0080.0000.0020.0000.0110.0000.0260.016
joining_month-0.0040.0000.005-0.0040.0000.0000.0140.0130.0000.0120.0000.0120.0000.0000.0020.0130.0020.0220.0071.0000.019-0.0030.005-0.0060.0090.0080.0000.0000.0080.0200.0000.0000.0090.0000.0040.0110.0000.0050.0000.000
joining_year0.0080.0170.0000.0000.0000.0000.0000.0150.0000.0000.0000.0070.0000.0000.0090.0000.0130.0110.0000.0191.0000.0000.0120.0000.0110.0120.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.009
last_visit_time_hour-0.009-0.007-0.007-0.0020.0150.0120.0000.0100.0000.0220.0000.0040.0200.0000.0000.0000.0000.0000.002-0.0030.0001.000-0.0050.0020.0000.0000.0000.0150.0000.0160.0000.0000.0000.0000.0090.0000.0070.0000.0000.000
last_visit_time_minutes0.0090.0080.0060.0050.0130.0130.0000.0000.0000.0020.0000.0000.0240.0160.0000.0000.0000.000-0.0050.0050.012-0.0051.0000.0060.0080.0120.0070.0000.0000.0100.0000.0230.0100.000-0.0040.0000.0160.0110.0100.010
last_visit_time_seconds0.0020.0060.003-0.0000.0000.0000.0150.0000.0140.0000.0000.0000.0070.0000.0000.0060.0190.000-0.001-0.0060.0000.0020.0061.0000.0000.0000.0000.0070.0000.0080.0000.0240.0000.0000.0020.0180.0000.0000.0090.000
medium_of_operation_Both0.0100.2030.0090.0000.0150.0080.0000.0030.0110.0000.0000.0110.0000.0000.0000.0000.0510.0570.0000.0090.0110.0000.0080.0001.0000.2650.2630.0000.0000.0120.0060.0000.0540.0000.0000.0000.0000.0080.0060.048
medium_of_operation_Desktop0.0110.0540.0200.0000.0000.0000.0090.0120.0090.0070.0150.0070.0000.0020.0000.0000.0080.0110.0000.0080.0120.0000.0120.0000.2651.0000.5950.0000.0000.0000.0010.0000.0120.0070.0000.0090.0000.0000.0000.012
medium_of_operation_Smartphone0.0080.0680.0230.0000.0000.0070.0090.0160.0150.0120.0130.0170.0050.0030.0040.0000.0160.0180.0000.0000.0060.0000.0070.0000.2630.5951.0000.0000.0000.0140.0080.0000.0250.0060.0000.0150.0000.0000.0000.013
membership_category_Gold Membership0.0000.0120.0760.0000.0110.0260.0280.0550.0520.0640.0240.0380.0000.0070.0130.0000.0030.0000.0100.0000.0000.0150.0000.0070.0000.0000.0001.0000.2460.1780.1760.2100.0000.0000.0790.0000.0000.0000.0070.007
membership_category_No Membership0.0130.0120.1470.0000.0530.0440.0370.1020.1010.1030.0320.0960.0000.0050.0050.0000.0160.0150.0150.0080.0000.0000.0000.0000.0000.0000.0000.2461.0000.1890.1870.2230.0000.0000.1520.0080.0170.0000.0040.010
membership_category_Platinum Membership0.0000.0220.1560.0000.0400.0370.0500.1050.0920.1170.0380.1160.0030.0000.0170.0100.0000.0170.0180.0200.0000.0160.0100.0080.0120.0000.0140.1780.1891.0000.1350.1610.0000.0000.1400.0000.0000.0120.0000.010
membership_category_Premium Membership0.0000.0000.1630.0000.0520.0510.0320.1130.1200.1040.0390.0990.0000.0000.0000.0000.0310.0230.0000.0000.0000.0000.0000.0000.0060.0010.0080.1760.1870.1351.0000.1600.0260.0000.1310.0150.0340.0090.0160.007
membership_category_Silver Membership0.0000.0000.0400.0090.0030.0180.0120.0250.0200.0370.0000.0180.0000.0020.0120.0140.0000.0100.0000.0000.0000.0000.0230.0240.0000.0000.0000.2100.2230.1610.1601.0000.0070.0000.0410.0100.0130.0000.0000.000
offer_application_preference_Yes0.0000.0710.0400.0100.0000.0080.0130.0170.0280.0210.0190.0370.0000.0000.0000.0130.0000.0120.0080.0090.0000.0000.0100.0000.0540.0120.0250.0000.0000.0000.0260.0071.0000.0000.0170.0100.0000.0000.0000.818
past_complaint_Yes0.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0060.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0050.000
points_in_wallet0.0220.0150.094-0.0200.0520.0540.0540.1320.1430.1450.0600.1300.0160.0000.0140.0000.0250.0230.0020.0040.0000.009-0.0040.0020.0000.0000.0000.0790.1520.1400.1310.0410.0170.0001.0000.0250.0270.0000.0000.011
preferred_offer_types_Gift Vouchers/Coupons0.0040.0000.0480.0000.0210.0190.0050.0360.0300.0310.0000.0330.0000.0000.0040.0090.0000.0000.0000.0110.0000.0000.0000.0180.0000.0090.0150.0000.0080.0000.0150.0100.0100.0000.0251.0000.5020.0000.0000.016
preferred_offer_types_Without Offers0.0090.0000.0530.0000.0340.0110.0130.0360.0430.0400.0000.0280.0000.0000.0210.0090.0000.0000.0110.0000.0030.0070.0160.0000.0000.0000.0000.0000.0170.0000.0340.0130.0000.0000.0270.5021.0000.0000.0000.000
region_category_Town0.0000.0000.0000.0000.0030.0000.0000.0000.0090.0080.0000.0000.0000.0000.0000.0000.0070.0000.0000.0050.0000.0000.0110.0000.0080.0000.0000.0000.0000.0120.0090.0000.0000.0000.0000.0000.0001.0000.4070.000
region_category_Village0.0000.0110.0430.0000.0030.0000.0050.0190.0230.0280.0100.0110.0050.0000.0000.0000.0000.0000.0260.0000.0000.0000.0100.0090.0060.0000.0000.0070.0040.0000.0160.0000.0000.0050.0000.0000.0000.4071.0000.000
used_special_discount_Yes0.0000.0730.0100.0030.0120.0000.0000.0110.0000.0000.0110.0100.0000.0000.0000.0060.0200.0190.0160.0000.0090.0000.0100.0000.0480.0120.0130.0070.0100.0100.0070.0000.8180.0000.0110.0160.0000.0000.0001.000

Missing values

2025-03-01T13:48:05.317181image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-03-01T13:48:05.810497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

agedays_since_last_loginavg_time_spentavg_transaction_valuepoints_in_walletjoining_dayjoining_monthjoining_yearlast_visit_time_hourlast_visit_time_minuteslast_visit_time_secondsgender_Mgender_Unknownregion_category_Townregion_category_Villagemembership_category_Gold Membershipmembership_category_No Membershipmembership_category_Platinum Membershipmembership_category_Premium Membershipmembership_category_Silver Membershipjoined_through_referral_Nojoined_through_referral_Yespreferred_offer_types_Gift Vouchers/Couponspreferred_offer_types_Without Offersmedium_of_operation_Bothmedium_of_operation_Desktopmedium_of_operation_Smartphoneinternet_option_Mobile_Datainternet_option_Wi-Fiused_special_discount_Yesoffer_application_preference_Yespast_complaint_Yesfeedback_Poor Customer Servicefeedback_Poor Product Qualityfeedback_Poor Websitefeedback_Products always in Stockfeedback_Quality Customer Carefeedback_Reasonable Pricefeedback_Too many adsfeedback_User Friendly Website
05012386.2640721.44733.830000211201571930FalseFalseFalseTrueFalseFalseFalseTrueFalseTrueFalseFalseTrueFalseFalseTrueFalseTrueTrueFalseFalseFalseTrueFalseFalseFalseFalseFalseFalse
1411137.809644.40726.000000132016222116TrueFalseFalseTrueTrueFalseFalseFalseFalseTrueFalseFalseTrueFalseTrueFalseFalseFalseTrueFalseFalseFalseFalseTrueFalseFalseFalseFalseFalse
23118215.363693.25713.780000332017164039FalseFalseTrueFalseFalseFalseFalseFalseTrueTrueFalseTrueFalseTrueFalseFalseTrueFalseTrueFalseTrueFalseFalseFalseFalseFalseFalseFalseFalse
364-99944.5736809.56744.9700001882017145617TrueFalseTrueFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseFalseFalseFalseFalseTrueFalse
4166349.8840675.86299.04835155201525753FalseFalseTrueFalseFalseTrueFalseFalseFalseFalseTrueFalseTrueFalseFalseTrueTrueFalseFalseTrueTrueFalseFalseTrueFalseFalseFalseFalseFalse
517-99931.029948.54577.830000412201684554TrueFalseTrueFalseFalseFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseFalseTrueFalseTrueFalseTrueFalseTrueFalseFalseFalseFalseFalseFalse
61715262.5892825.88685.9687941692015104033TrueFalseFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseFalseFalseTrueFalseFalseTrueTrueFalseFalseFalseFalseFalseFalseFalseTrueFalseFalse
7173258.945993.19602.6000002392017132630TrueFalseTrueFalseFalseFalseFalseFalseFalseFalseTrueFalseTrueFalseTrueFalseFalseFalseTrueFalseTrueFalseFalseFalseFalseFalseFalseTrueFalse
85814408.741549.87727.610000462015134411FalseFalseTrueFalseFalseFalseFalseFalseTrueTrueFalseFalseFalseFalseTrueFalseFalseTrueFalseTrueFalseFalseFalseFalseFalseFalseFalseTrueFalse
922430.2519363.60528.6600001410201510441TrueFalseTrueFalseFalseTrueFalseFalseFalseFalseTrueFalseFalseFalseTrueFalseFalseFalseTrueFalseFalseFalseFalseTrueFalseFalseFalseFalseFalse
agedays_since_last_loginavg_time_spentavg_transaction_valuepoints_in_walletjoining_dayjoining_monthjoining_yearlast_visit_time_hourlast_visit_time_minuteslast_visit_time_secondsgender_Mgender_Unknownregion_category_Townregion_category_Villagemembership_category_Gold Membershipmembership_category_No Membershipmembership_category_Platinum Membershipmembership_category_Premium Membershipmembership_category_Silver Membershipjoined_through_referral_Nojoined_through_referral_Yespreferred_offer_types_Gift Vouchers/Couponspreferred_offer_types_Without Offersmedium_of_operation_Bothmedium_of_operation_Desktopmedium_of_operation_Smartphoneinternet_option_Mobile_Datainternet_option_Wi-Fiused_special_discount_Yesoffer_application_preference_Yespast_complaint_Yesfeedback_Poor Customer Servicefeedback_Poor Product Qualityfeedback_Poor Websitefeedback_Products always in Stockfeedback_Quality Customer Carefeedback_Reasonable Pricefeedback_Too many adsfeedback_User Friendly Website
19909422510.5952128.14827.300000172201663433FalseFalseFalseTrueFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalse
19910522431.0730663.68773.850000210201681638FalseFalseTrueFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseTrueFalse
19911261733.0445911.38649.870000117201510551FalseFalseTrueFalseFalseTrueFalseFalseFalseTrueFalseTrueFalseFalseTrueFalseFalseFalseTrueFalseTrueFalseFalseTrueFalseFalseFalseFalseFalse
1991259-99943.3625428.68796.360000141120160342TrueFalseFalseFalseFalseFalseFalseFalseTrueTrueFalseTrueFalseFalseTrueFalseFalseTrueFalseTrueTrueFalseFalseTrueFalseFalseFalseFalseFalse
199135811113.6310004.18622.46000057201522122TrueFalseFalseTrueTrueFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueFalseFalseTrueFalseTrueFalseFalseFalseTrueFalseFalseFalseFalseFalse
199141216103.5746279.35708.120000251201503243TrueFalseTrueFalseTrueFalseFalseFalseFalseTrueFalseFalseTrueFalseTrueFalseFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseFalseFalse
19915402163.1923466.26574.3400003112201775437FalseFalseFalseTrueFalseTrueFalseFalseFalseFalseTrueFalseTrueFalseTrueFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalseFalseFalse
19916551868.7217903.75564.30000099201592637TrueFalseTrueFalseFalseTrueFalseFalseFalseTrueFalseFalseFalseFalseTrueFalseTrueFalseFalseTrueTrueFalseFalseFalseFalseFalseFalseFalseFalse
19917173119.5414057.09606.3400001742016215914FalseFalseFalseFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseFalseFalseTrueFalseFalseFalseTrueFalseFalseFalseTrueFalseFalseFalseFalseFalse
19918208505.2636786.441193.68981330102017105015TrueFalseTrueFalseFalseFalseFalseTrueFalseFalseTrueTrueFalseTrueFalseFalseFalseTrueFalseTrueTrueFalseFalseFalseFalseFalseFalseTrueFalse